{"id":"https://openalex.org/W3081646140","doi":"https://doi.org/10.1142/s0218194020400124","title":"A Data-Driven Two-Stage Prediction Model for Train Primary-Delay Recovery Time","display_name":"A Data-Driven Two-Stage Prediction Model for Train Primary-Delay Recovery Time","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3081646140","doi":"https://doi.org/10.1142/s0218194020400124","mag":"3081646140"},"language":"en","primary_location":{"id":"doi:10.1142/s0218194020400124","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194020400124","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024445768","display_name":"Bowen Gao","orcid":"https://orcid.org/0000-0002-2758-6377"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bowen Gao","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017101734","display_name":"Dongxiu Ou","orcid":"https://orcid.org/0000-0002-2415-3058"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiu Ou","raw_affiliation_strings":["Shanghai Key Laboratory of Rail Infrastructure, Durability and System Safety, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Key Laboratory of Rail Infrastructure, Durability and System Safety, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101442778","display_name":"Decun Dong","orcid":"https://orcid.org/0000-0002-1585-1882"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Decun Dong","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040535296","display_name":"Yusen Wu","orcid":"https://orcid.org/0000-0003-4235-8708"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yusen Wu","raw_affiliation_strings":["The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, P.\u00a0R.\u00a0China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":1.2467,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.82914531,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":97},"biblio":{"volume":"30","issue":"07","first_page":"921","last_page":"940"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10842","display_name":"Railway Engineering and Dynamics","score":0.9951000213623047,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7156645059585571},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.682554304599762},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6173831224441528},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5540578961372375},{"id":"https://openalex.org/keywords/predictive-modelling","display_name":"Predictive modelling","score":0.4946562945842743},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.4714910686016083},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4386654496192932},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41113558411598206},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.389822781085968},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.36969947814941406}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156645059585571},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.682554304599762},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6173831224441528},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5540578961372375},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.4946562945842743},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.4714910686016083},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4386654496192932},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41113558411598206},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.389822781085968},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.36969947814941406},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218194020400124","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218194020400124","pdf_url":null,"source":{"id":"https://openalex.org/S131442419","display_name":"International Journal of Software Engineering and Knowledge Engineering","issn_l":"0218-1940","issn":["0218-1940","1793-6403"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Software Engineering and Knowledge Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1510526001","https://openalex.org/W1678356000","https://openalex.org/W1988604380","https://openalex.org/W2004147962","https://openalex.org/W2028526723","https://openalex.org/W2028958679","https://openalex.org/W2082280082","https://openalex.org/W2110435420","https://openalex.org/W2148714761","https://openalex.org/W2330820318","https://openalex.org/W2344633803","https://openalex.org/W2504252576","https://openalex.org/W2522225365","https://openalex.org/W2603457432","https://openalex.org/W2614696754","https://openalex.org/W2790747112","https://openalex.org/W2911964244","https://openalex.org/W2936650651"],"related_works":["https://openalex.org/W4321636153","https://openalex.org/W4224946860","https://openalex.org/W4313640622","https://openalex.org/W3210918776","https://openalex.org/W1996541855","https://openalex.org/W3195168932","https://openalex.org/W4383535405","https://openalex.org/W4281887347","https://openalex.org/W4323356248","https://openalex.org/W3198510570"],"abstract_inverted_index":{"Accurate":[0],"prediction":[1,24,64,97],"of":[2,33,56,66,83,91,161,179],"train":[3,34],"delay":[4,177,192],"recovery":[5,31],"is":[6,26,75,137,146,181],"critical":[7],"for":[8],"railway":[9],"incident":[10],"management":[11],"and":[12,59,85,125,196],"providing":[13],"passengers":[14],"with":[15,109],"accurate":[16],"journey":[17],"time.":[18],"In":[19,45],"this":[20],"paper,":[21],"a":[22,182],"two-stage":[23],"model":[25,60,105,154],"proposed":[27,104,153],"to":[28,52,87,148,158],"predict":[29],"the":[30,38,54,63,80,88,96,103,144,152,159,176],"time":[32,68],"primary-delay":[35],"based":[36],"on":[37,62,190],"real":[39],"records":[40],"from":[41],"High-Speed":[42],"Railway":[43],"(HSR).":[44],"Stage":[46],"1,":[47],"two":[48],"models":[49],"are":[50],"built":[51],"study":[53,187],"influence":[55],"feature":[57],"space":[58],"framework":[61],"accuracy":[65,98,160],"buffer":[67],"in":[69,171],"each":[70],"section":[71],"or":[72],"station.":[73],"It":[74,163],"found":[76],"that":[77,133,165],"explicitly":[78],"inputting":[79],"attribute":[81],"features":[82],"stations":[84],"sections":[86],"model,":[89],"instead":[90],"implicit":[92],"simulation,":[93],"will":[94,188],"improve":[95],"effectively.":[99],"For":[100],"validation":[101],"purpose,":[102],"has":[106,168],"been":[107],"compared":[108],"several":[110],"alternative":[111],"models,":[112],"namely,":[113],"Logistic":[114],"Regression":[115],"(LR),":[116],"Artificial":[117],"Neutral":[118],"Network":[119],"(ANN),":[120],"Support":[121],"Vector":[122],"Machine":[123],"(SVM)":[124],"Gradient":[126],"Boosting":[127],"Tree":[128],"(GBT).":[129],"The":[130],"results":[131],"show":[132],"its":[134],"remarkable":[135],"performance":[136],"better":[138],"than":[139],"other":[140],"schemes.":[141],"Specifically,":[142],"when":[143],"error":[145],"extended":[147],"3[Formula:":[149],"see":[150],"text]min,":[151],"can":[155],"achieve":[156],"up":[157],"94.63%.":[162],"proves":[164],"our":[166,185],"method":[167],"high":[169],"value":[170],"practical":[172],"engineering":[173],"application.":[174],"Considering":[175],"propagation":[178,193],"trains":[180],"complex":[183],"process,":[184],"future":[186],"focus":[189],"building":[191],"knowledge":[194,199],"base":[195],"dispatcher":[197],"experience":[198],"base.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}
